An exclusion list based label-free proteome quantification approach using an LTQ Orbitrap

Evaluating Peptide Fragment Ion Detection Using Traveling Wave Ion Mobility Spectrometry with Signal-Enhanced MSE (SEMSE)

The inherent poor sampling of fragment ions in time-of-flight mass analyzers was recently improved for data-dependent acquisition (DDA) by considering their drift times in traveling wave ion mobility spectrometry (TWIMS). Here, we extend this TWIMS-DDA approach to the data-independent acquisition (DIA) mode MS^E to improve the signal intensities of fragment ions by providing improved ion beam sampling efficiency, which we termed therefore signal-enhanced MS^E (SEMS^E). The theoretical expectation that SEMS^E improves the number of identified peptides, the number of quantifiable peptides, and the lower limit of quantitation in wideband DIA was evaluated on an electrospray ionisation-ion mobility spectrometry-quadrupole-time-of-flight-MS (ESI-IMS-Q-TOF-MS) (Synapt G2-Si) in comparison to five established TWIMS-DDA and TWIMS-MS^E methods with respect to the number of peptide identifications, the spectral quality of supporting peptide spectra matches, and (most importantly) fragment ion signal sensitivity. A comparison of the fragment signals clearly indicated that SEMS^E provides 6.8- to 11.5-fold larger peak areas than established MS^E techniques. While this clearly shows the advantages of SEMS^E, the inherent limitations of the current software tools do not allow using all benefits in routine analyses. As the simultaneous fragmentation of co-eluting peptides limited peptide identification, DDA and MS^E data sets were integrated using Skyline.

Metabolic Rearrangements Causing Elevated Proline and Polyhydroxybutyrate Accumulation During the Osmotic Adaptation Response of Bacillus megaterium

For many years now, Bacillus megaterium serves as a microbial workhorse for the high-level production of recombinant proteins in the g/L-scale. However, efficient and stable production processes require the knowledge of the molecular adaptation strategies of the host organism to establish optimal environmental conditions. Here, we interrogated the osmotic stress response of B. megaterium using transcriptome, proteome, metabolome, and fluxome analyses. An initial transient adaptation consisted of potassium import and glutamate counterion synthesis. The massive synthesis of the compatible solute proline constituted the second longterm adaptation process. Several stress response enzymes involved in iron scavenging and reactive oxygen species (ROS) fighting proteins showed higher levels under prolonged osmotic stress induced by 1.8 M NaCl. At the same time, the downregulation of the expression of genes of the upper part of glycolysis resulted in the activation of the pentose phosphate pathway (PPP), generating an oversupply of NADPH. The increased production of lactate accompanied by the reduction of acetate secretion partially compensate for the unbalanced (NADH/NAD⁺) ratio. Besides, the tricarboxylic acid cycle (TCA) mainly supplies the produced NADH, as indicated by the higher mRNA and protein levels of involved enzymes, and further confirmed by ¹³C flux analyses. As a consequence of the metabolic flux toward acetyl-CoA and the generation of an excess of NADPH, B. megaterium redirected the produced acetyl-CoA toward the polyhydroxybutyrate (PHB) biosynthetic pathway accumulating around 30% of the cell dry weight (CDW) as PHB. This direct relation between osmotic stress and intracellular PHB content has been evidenced for the first time, thus opening new avenues for synthesizing this valuable biopolymer using varying salt concentrations under non-limiting nutrient conditions.

Detailed Soluble Proteome Analyses of a Dairy-Isolated Enterococcus faecalis: A Possible Approach to Assess Food Safety and Potential Probiotic Value

Enterococci are common inhabitants of the gastrointestinal tracts of humans and animals and thanks to their capability to tolerate different environmental conditions and their high rates of gene transfer, they are able to colonize various ecological niches, as food matrices. Enterococcus faecalis bacteria are defined as controversial microorganisms. From one side they are used as food starters, bio-control agents and probiotics to improve human or animal health. From the other side, in the last two decades enterococci have emerged as important nosocomial pathogens, because bearing high-level of resistance to antibiotics and several putative virulence factors. In this study, the soluble proteome quantitation data (LC-MS/MS) of the food-isolated strain E. faecalis D27 (dairy-isolate) was compared with the soluble proteome quantitation data of the pathogenic E. faecalis UW3114 (urinary tract infection isolate) and with the one of the health promoting strain E. faecalis Symbioflor1, respectively. The comparison of cytosolic protein expression profiles highlighted statistically significant changes in the abundance of proteins mainly involved in specific metabolic pathways, nutrient transport, stress response, and cell wall modulation. Moreover, especially in the dairy isolate and the clinical isolate, several proteins with potential pathogenic implications were found, such as serine proteases, von Willebrand factor, serine hydrolase with beta lactamase activity, efflux transporter, and proteins involved in horizontal gene transfer. The analysis of the extracellular proteome provided interesting results concerning proteins involved in bacterial communication, such as pheromones and conjugative elements and also proteins able to interact with human components. The phenotypic characterization evaluating (i) biofilm formation (ii) hemolytic activity on blood agar plates (iii) protease activity (iv) gelatinase (v) antibiotic resistance pattern, enabled us to elucidate the risks associated with the poor characterized foodborne E. faecalis D27.

A homopolymeric adenosine tract in the promoter region of nspA influences factor H-mediated serum resistance in Neisseria meningitidis

Although usually asymptomatically colonizing the human nasopharynx, the Gram-negative bacterium Neisseria meningitidis (meningococcus) can spread to the blood stream and cause invasive disease. For survival in blood, N. meningitidis evades the complement system by expression of a polysaccharide capsule and surface proteins sequestering the complement regulator factor H (fH). Meningococcal strains belonging to the sequence type (ST-) 41/44 clonal complex (cc41/44) cause a major proportion of serogroup B meningococcal disease worldwide, but they are also common in asymptomatic carriers. Proteome analysis comparing cc41/44 isolates from invasive disease versus carriage revealed differential expression levels of the outer membrane protein NspA, which binds fH. Deletion of nspA reduced serum resistance and NspA expression correlated with fH sequestration. Expression levels of NspA depended on the length of a homopolymeric tract in the nspA promoter: A 5-adenosine tract dictated low NspA expression, whereas a 6-adenosine motif guided high NspA expression. Screening German cc41/44 strain collections revealed the 6-adenosine motif in 39% of disease isolates, but only in 3.4% of carriage isolates. Thus, high NspA expression is associated with disease, but not strictly required. The 6-adenosine nspA promoter is most common to the cc41/44, but is also found in other hypervirulent clonal complexes.

Comparative proteome analysis in an Escherichia coli CyDisCo strain identifies stress responses related to protein production, oxidative stress and accumulation of misfolded protein

Background

The Twin-arginine translocation (Tat) pathway of Escherichia coli has great potential for the export of biopharmaceuticals to the periplasm due to its ability to transport folded proteins, and its proofreading mechanism that allows correctly folded proteins to translocate. Coupling the Tat-dependent protein secretion with the formation of disulfide bonds in the cytoplasm of E. coli CyDisCo provides a powerful platform for the production of industrially challenging proteins. In this study, we investigated the effects on the E. coli cells of exporting a folded substrate (scFv) to the periplasm using a Tat signal peptide, and the effects of expressing an export-incompetent misfolded variant.

Results

Cell growth is decreased when either the correctly folded or misfolded scFv is expressed with a Tat signal peptide. However, only the production of misfolded scFv leads to cell aggregation and formation of inclusion bodies. The comprehensive proteomic analysis revealed that both conditions, recombinant protein overexpression and misfolded protein accumulation, lead to downregulation of membrane transporters responsible for protein folding and insertion into the membrane while upregulating the production of chaperones and proteases involved in removing aggregates. These conditions also differentially affect the production of transcription factors and proteins involved in DNA replication. The most distinct stress response observed was the cell aggregation caused by elevated levels of antigen 43. Finally, Tat-dependent secretion causes an increase in tatA expression only after induction of protein expression, while the subsequent post-induction analysis revealed lower tatA and tatB expression levels, which correlate with lowered TatA and TatB protein abundance.

Conclusions

The study identified characteristic changes occurring as a result of the production of both a folded and a misfolded protein, but also highlights an exclusive unfolded stress response. Countering and compensating for these changes may result in higher yields of pharmaceutically relevant proteins exported to the periplasm.

Electronic supplementary material

The online version of this article (10.1186/s12934-019-1071-7) contains supplementary material, which is available to authorized users.

Exploiting fine-scale genetic and physiological variation of closely related microbes to reveal unknown enzyme functions

Polysaccharide degradation by marine microbes represents one of the largest and most rapid heterotrophic transformations of organic matter in the environment. Microbes employ systems of complementary carbohydrate-specific enzymes to deconstruct algal or plant polysaccharides (glycans) into monosaccharides. Because of the high diversity of glycan substrates, the functions of these enzymes are often difficult to establish. One solution to this problem may lie within naturally occurring microdiversity; varying numbers of enzymes, due to gene loss, duplication, or transfer, among closely related environmental microbes create metabolic differences akin to those generated by knock-out strains engineered in the laboratory used to establish the functions of unknown genes. Inspired by this natural fine-scale microbial diversity, we show here that it can be used to develop hypotheses guiding biochemical experiments for establishing the role of these enzymes in nature. In this work, we investigated alginate degradation among closely related strains of the marine bacterium Vibrio splendidus One strain, V. splendidus 13B01, exhibited high extracellular alginate lyase activity compared with other V. splendidus strains. To identify the enzymes responsible for this high extracellular activity, we compared V. splendidus 13B01 with the previously characterized V. splendidus 12B01, which has low extracellular activity and lacks two alginate lyase genes present in V. splendidus 13B01. Using a combination of genomics, proteomics, biochemical, and functional screening, we identified a polysaccharide lyase family 7 enzyme that is unique to V. splendidus 13B01, secreted, and responsible for the rapid digestion of extracellular alginate. These results demonstrate the value of querying the enzymatic repertoires of closely related microbes to rapidly pinpoint key proteins with beneficial functions.

Fungal volatile compounds induce production of the secondary metabolite Sodorifen in Serratia plymuthica PRI-2C

The ability of bacteria and fungi to communicate with each other is a remarkable aspect of the microbial world. It is recognized that volatile organic compounds (VOCs) act as communication signals, however the molecular responses by bacteria to fungal VOCs remain unknown. Here we perform transcriptomics and proteomics analyses of Serratia plymuthica PRI-2C exposed to VOCs emitted by the fungal pathogen Fusarium culmorum. We find that the bacterium responds to fungal VOCs with changes in gene and protein expression related to motility, signal transduction, energy metabolism, cell envelope biogenesis, and secondary metabolite production. Metabolomic analysis of the bacterium exposed to the fungal VOCs, gene cluster comparison, and heterologous co-expression of a terpene synthase and a methyltransferase revealed the production of the unusual terpene sodorifen in response to fungal VOCs. These results strongly suggest that VOCs are not only a metabolic waste but important compounds in the long-distance communication between fungi and bacteria.

Proteomic Approach for Extracting Cytoplasmic Proteins from Streptococcus sanguinis using Mass Spectrometry

Streptococcus sanguinis is a commensal and early colonizer of oral cavity as well as an opportunistic pathogen of infectious endocarditis. Extracting the soluble proteome of this bacterium provides deep insights about the physiological dynamic changes under different growth and stress conditions, thus defining "proteomic signatures" as targets for therapeutic intervention. In this protocol, we describe an experimentally verified approach to extract maximal cytoplasmic proteins from Streptococcus sanguinis SK36 strain. A combination of procedures was adopted that broke the thick cell wall barrier and minimized denaturation of the intracellular proteome, using optimized buffers and a sonication step. Extracted proteome was quantitated using Pierce BCA Protein Quantitation assay and protein bands were macroscopically assessed by Coomassie Blue staining. Finally, a high resolution detection of the extracted proteins was conducted through Synapt G2Si mass spectrometer, followed by label-free relative quantification via Progenesis QI. In conclusion, this pipeline for proteomic extraction and analysis of soluble proteins provides a fundamental tool in deciphering the biological complexity of Streptococcus sanguinis.

Nitrogen fixation in a chemoautotrophic lucinid symbiosis

The shallow water bivalve Codakia orbicularis lives in symbiotic association with a sulfur-oxidizing bacterium in its gills. The endosymbiont fixes CO₂ and thus generates organic carbon compounds, which support the host's growth. To investigate the uncultured symbiont's metabolism and symbiont-host interactions in detail we conducted a proteogenomic analysis of purified bacteria. Unexpectedly, our results reveal a hitherto completely unrecognized feature of the C. orbicularis symbiont's physiology: the symbiont's genome encodes all proteins necessary for biological nitrogen fixation (diazotrophy). Expression of the respective genes under standard ambient conditions was confirmed by proteomics. Nitrogenase activity in the symbiont was also verified by enzyme activity assays. Phylogenetic analysis of the bacterial nitrogenase reductase NifH revealed the symbiont's close relationship to free-living nitrogen-fixing Proteobacteria from the seagrass sediment. The C. orbicularis symbiont, here tentatively named 'Candidatus Thiodiazotropha endolucinida', may thus not only sustain the bivalve's carbon demands. C. orbicularis may also benefit from a steady supply of fixed nitrogen from its symbiont-a scenario that is unprecedented in comparable chemoautotrophic symbioses.

Costs of life - Dynamics of the protein inventory of Staphylococcus aureus during anaerobiosis

Absolute protein quantification was applied to follow the dynamics of the cytoplasmic proteome of Staphylococcus aureus in response to long-term oxygen starvation. For 1,168 proteins, the majority of all expressed proteins, molecule numbers per cell have been determined to monitor the cellular investments in single branches of bacterial life for the first time. In the presence of glucose the anaerobic protein pattern is characterized by increased amounts of glycolytic and fermentative enzymes such as Eno, GapA1, Ldh1, and PflB. Interestingly, the ferritin-like protein FtnA belongs to the most abundant proteins during anaerobic growth. Depletion of glucose finally leads to an accumulation of different enzymes such as ArcB1, ArcB2, and ArcC2 involved in arginine deiminase pathway. Concentrations of 29 exo- and 78 endometabolites were comparatively assessed and have been integrated to the metabolic networks. Here we provide an almost complete picture on the response to oxygen starvation, from signal transduction pathways to gene expression pattern, from metabolic reorganization after oxygen depletion to beginning cell death and lysis after glucose exhaustion. This experimental approach can be considered as a proof of principle how to combine cell physiology with quantitative proteomics for a new dimension in understanding simple life processes as an entity.

Exosomes in the nose induce immune cell trafficking and harbour an altered protein cargo in chronic airway inflammation

Background

Exosomes are nano-sized extracellular vesicles participating in cell-to-cell communication both in health and disease. However, the knowledge about the functions and molecular composition of exosomes in the upper airways is limited. The aim of the current study was therefore to determine whether nasal exosomes can influence inflammatory cells and to establish the proteome of nasal lavage fluid-derived exosomes in healthy subjects, as well as its alterations in individuals with chronic airway inflammatory diseases [asthma and chronic rhinosinusitis (CRS)].

Methods

Nasal lavage fluid was collected from 14 healthy subjects, 15 subjects with asthma and 13 subjects with asthma/CRS. Exosomes were isolated with differential centrifugation and the proteome was analysed by LC–MS/MS with the application of two exclusion lists as well as using quantitative proteomics. Ingenuity Pathways Analysis and GO Term finder was used to predict the functions associated with the exosomal proteome and a migration assay was used to analyse the effect on immune cells by nasal exosomes.

Results

Firstly, we demonstrate that nasal exosomes can induce migration of several immune cells, such as monocytes, neutrophils and NK cells in vitro. Secondly, a mass spectrometry approach, with the application of exclusion lists, was utilised to generate a comprehensive protein inventory of the exosomes from healthy subjects. The use of exclusion lists resulted in the identification of ~15 % additional proteins, and increased the confidence in ~20 % of identified proteins. In total, 604 proteins were identified in nasal exosomes and the nasal exosomal proteome showed strong associations with immune-related functions, such as immune cell trafficking. Thirdly, a quantitative proteomics approach was used to determine alterations in the exosome proteome as a result of airway inflammatory disease. Serum-associated proteins and mucins were more abundant in the exosomes from subjects with respiratory diseases compared to healthy controls while proteins with antimicrobial functions and barrier-related proteins had decreased expression.

Conclusions

Nasal exosomes were shown to induce the migration of innate immune cells, which may be important as the airway epithelium is the first line of defence against pathogens and allergens. The decreased expression in barrier and antimicrobial exosomal proteins in subjects with airway diseases, could possibly contribute to an increased susceptibility to infections, which have important clinical implications in disease progression.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-016-0927-4) contains supplementary material, which is available to authorized users.

Shotgun proteomics of bacterial pathogens: advances, challenges and clinical implications

Mass spectrometry-based proteomics is increasingly used in analysis of bacterial pathogens. Simple experimental set-ups based on high accuracy mass spectrometry and powerful biochemical and bioinformatics tools are capable of reliably quantifying levels of several thousand bacterial proteins in a single experiment, reaching the analytical capacity to completely map whole proteomes. Here the authors present the state-of-the-art in bacterial pathogen proteomics and discuss challenges that the field is facing, especially in analysis of low abundant, modified proteins from organisms that are difficult to culture. Constant improvements in speed and sensitivity of mass spectrometers, as well as in bioinformatic and biochemical workflows will soon allow for comprehensive analysis of regulatory mechanisms of pathogenicity and enable routine application of proteomics in the clinical setting.

Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer

The promises of data-independent acquisition (DIA) strategies are a comprehensive and reproducible digital qualitative and quantitative record of the proteins present in a sample. We developed a fast and robust DIA method for comprehensive mapping of the urinary proteome that enables large scale urine proteomics studies. Compared to a data-dependent acquisition (DDA) experiments, our DIA assay doubled the number of identified peptides and proteins per sample at half the coefficients of variation observed for DDA data (DIA = ∼8%; DDA = ∼16%). We also tested different spectral libraries and their effects on overall protein and peptide identifications and their reproducibilities, which provided clear evidence that sample type-specific spectral libraries are preferred for reliable data analysis. To show applicability for biomarker discovery experiments, we analyzed a sample set of 87 urine samples from children seen in the emergency department with abdominal pain. The whole set was analyzed with high proteome coverage (∼1300 proteins/sample) in less than 4 days. The data set revealed excellent biomarker candidates for ovarian cyst and urinary tract infection. The improved throughput and quantitative performance of our optimized DIA workflow allow for the efficient simultaneous discovery and verification of biomarker candidates without the requirement for an early bias toward selected proteins.

A peptide resource for the analysis of Staphylococcus aureus in host-pathogen interaction studies

Staphylococcus aureus is an opportunistic human pathogen, which can cause life-threatening disease. Proteome analyses of the bacterium can provide new insights into its pathophysiology and important facets of metabolic adaptation and, thus, aid the recognition of targets for intervention. However, the value of such proteome studies increases with their comprehensiveness. We present an MS-driven, proteome-wide characterization of the strain S. aureus HG001. Combining 144 high precision proteomic data sets, we identified 19 109 peptides from 2088 distinct S. aureus HG001 proteins, which account for 72% of the predicted ORFs. Peptides were further characterized concerning pI, GRAVY, and detectability scores in order to understand the low peptide coverage of 8.7% (19 109 out of 220 245 theoretical peptides). The high quality peptide-centric spectra have been organized into a comprehensive peptide fragmentation library (SpectraST) and used for identification of S. aureus-typic peptides in highly complex host-pathogen interaction experiments, which significantly improved the number of identified S. aureus proteins compared to a MASCOT search. This effort now allows the elucidation of crucial pathophysiological questions in S. aureus-specific host-pathogen interaction studies through comprehensive proteome analysis. The S. aureus-specific spectra resource developed here also represents an important spectral repository for SRM or for data-independent acquisition MS approaches. All MS data have been deposited in the ProteomeXchange with identifier PXD000702 (http://proteomecentral.proteomexchange.org/dataset/PXD000702).

Impact of data-dependent exclusion list based mass spectrometry on label-free proteomic quantification

RATIONALE

Spectral count analysis via data-dependent acquisition (DDA) mode mass spectrometry is used as label-free protein quantification. However, combination of the DDA mode with exclusion list based DDA (DDA-EL) for the similar purpose has not yet been tested. Therefore, we have taken the initiative to check the protein abundance using DDA-EL and measured their suitability.

METHODS

To check the protein abundance correlation between different samples, multiple replicates of mass spectrometric analysis of peptides were conducted primarily in DDA mode. Subsequently, peptides were analyzed in multiple replicates in DDA-EL mode with an exclusion mass list prepared from the previous DDA analyses. The normalized spectral abundance factor (NSAF) for each identified protein was compared among replicated datasets of single DDA, DDA-EL, merged two DDAs, and merged DDA + DDA-EL or between different types of datasets.

RESULTS

A strong and linear NSAF correlation with an average correlation coefficient of 0.939 was observed in the comparison between each pair of DDA data. Similar connotation was also monitored in the comparison among DDA-EL data (r =0.928) or among merged DDA + DDA-EL data (r =0.960) while a reduced correlation coefficient (r =0.892) with increased deviation was marked between DDA and DDA-EL data.

CONCLUSIONS

Evaluation of protein abundance patterns from different cellular states can successfully be conducted by DDA-EL-based mass spectrometric analysis. Therefore, the new workflow, DDA-EL merged to DDA mode, is a potential alternative to protein identification and quantification method.

Quantitative proteomics in the field of microbiology

Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research.

Fur is the master regulator of the extraintestinal pathogenic Escherichia coli response to serum

Drug-resistant extraintestinal pathogenic Escherichia coli (ExPEC) strains are the major cause of colisepticemia (colibacillosis), a condition that has become an increasing public health problem in recent years. ExPEC strains are characterized by high resistance to serum, which is otherwise highly toxic to most bacteria. To understand how these bacteria survive and grow in serum, we performed system-wide analyses of their response to serum, making a clear distinction between the responses to nutritional immunity and innate immunity. Thus, mild heat inactivation of serum destroys the immune complement and abolishes the bactericidal effect of serum (inactive serum), making it possible to examine nutritional immunity. We used a combination of deep RNA sequencing and proteomics in order to characterize ExPEC genes whose expression is affected by the nutritional stress of serum and by the immune complement. The major change in gene expression induced by serum-active and inactive-involved metabolic genes. In particular, the serum metabolic response is coordinated by three transcriptional regulators, Fur, BasR, and CysB. Fur alone was responsible for more than 80% of the serum-induced transcriptional response. Consistent with its role as a major serum response regulator, deletion of Fur renders the bacteria completely serum sensitive. These results highlight the role of metabolic adaptation in colisepticemia and virulence.

IMPORTANCE

Drug-resistant extraintestinal pathogenic Escherichia coli (ExPEC) strains have emerged as major pathogens, especially in community- and hospital-acquired infections. These bacteria cause a large spectrum of syndromes, the most serious of which is septicemia, a condition with a high mortality rate. These bacterial strains are characterized by high resistance to serum, otherwise highly toxic to most bacteria. To understand the basis of this resistance, we carried out system-wide analyses of the response of ExPEC strains to serum by using proteomics and deep RNA sequencing. The major changes in gene expression induced by exposure to serum involved metabolic genes, not necessarily implicated in relation to virulence. One metabolic regulator-Fur-involved in iron metabolism was responsible for more than 80% of the serum-induced response, and its deletion renders the bacteria completely serum sensitive. These results highlight the role of metabolic adaptation in virulence.

Unveiling novel interactions of histone chaperone Asf1 linked to TREX-2 factors Sus1 and Thp1

Anti-silencing function 1 (Asf1) is a conserved key eukaryotic histone H3/H4 chaperone that participates in a variety of DNA and chromatin-related processes. These include the assembly and disassembly of histones H3 and H4 from chromatin during replication, transcription, and DNA repair. In addition, Asf1 is required for H3K56 acetylation activity dependent on histone acetyltransferase Rtt109. Thus, Asf1 impacts on many aspects of DNA metabolism. To gain insights into the functional links of Asf1 with other cellular machineries, we employed mass spectrometry coupled to tandem affinity purification (TAP) to investigate novel physical interactions of Asf1. Under different TAP-MS analysis conditions, we describe a new repertoire of Asf1 physical interactions and novel Asf1 post-translational modifications as ubiquitination, methylation and acetylation that open up new ways to regulate Asf1 functions. Asf1 co-purifies with several subunits of the TREX-2, SAGA complexes, and with nucleoporins Nup2, Nup60, and Nup57, which are all involved in transcription coupled to mRNA export in eukaryotes. Reciprocally, Thp1 and Sus1 interact with Asf1. Albeit mRNA export and GAL1 transcription are not affected in asf1Δ a strong genetic interaction exists between ASF1 and SUS1. Notably, supporting a functional link between Asf1 and TREX-2, both Sus1 and Thp1 affect the levels of Asf1-dependent histone H3K56 acetylation and histone H3 and H4 incorporation onto chromatin. Additionally, we provide evidence for a role of Asf1 in histone H2B ubiquitination. This work proposes a functional link between Asf1 and TREX-2 components in histone metabolism at the vicinity of the nuclear pore complex.

In-depth profiling of the peripheral blood mononuclear cells proteome for clinical blood proteomics

Peripheral blood mononuclear cells (PBMCs) are an easy accessible cellular part of the blood organ and, along with platelets, represent the only site of active gene expression in blood. These cells undergo immunophenotypic changes in various diseases and represent a peripheral source of monitoring gene expression and posttranslational modifications relevant to many diseases. Little is known about the source of many blood proteins and we hypothesise that release from PBMCs through active and passive mechanisms may account for a substantial part of the plasma proteome. The use of state-of-the-art proteomic profiling methods in PBMCs will enable minimally invasive monitoring of disease progression or response to treatment and discovery of biomarkers. To achieve this goal, detailed mapping of the PBMC proteome using a sensitive, robust, and quantitative methodological setup is required. We have applied an indepth gel-free proteomics approach using tandem mass tags (TMT), unfractionated and SCX fractionated PBMC samples, and LC-MS/MS with various modulations. This study represents a benchmark in deciphering the PBMC proteome as we provide a deep insight by identifying 4129 proteins and 25503 peptides. The identified proteome defines the scope that enables PBMCs to be characterised as cellular major biomarker pool within the blood organ.

Extensive in vivo human milk peptidomics reveals specific proteolysis yielding protective antimicrobial peptides

Milk is traditionally considered an ideal source of the basic elemental nutrients required by infants. More detailed examination is revealing that milk represents a more functional ensemble of components with benefits to both infants and mothers. A comprehensive peptidomics method was developed and used to analyze human milk yielding an extensive array of protein products present in the fluid. Over 300 milk peptides were identified originating from major and many minor protein components of milk. As expected, the majority of peptides derived from β-casein, however no peptide fragments from the major milk proteins lactoferrin, α-lactalbumin, and secretory immunoglobulin A were identified. Proteolysis in the mammary gland is selective-released peptides were drawn only from specific proteins and typically from only select parts of the parent sequence. A large number of the peptides showed significant sequence overlap with peptides with known antimicrobial or immunomodulatory functions. Antibacterial assays showed the milk peptide mixtures inhibited the growth of Escherichia coli and Staphylococcus aureus . The predigestion of milk proteins and the consequent release of antibacterial peptides may provide a selective advantage through evolution by protecting both the mother's mammary gland and her nursing offspring from infection.

Cleaning up the masses: exclusion lists to reduce contamination with HPLC-MS/MS

Mass spectrometry, in the past five years, has increased in speed, accuracy and use. With the ability of the mass spectrometers to identify increasing numbers of proteins the identification of undesirable peptides (those not from the protein sample) has also increased. Most undesirable contaminants originate in the laboratory and come from either the user (e.g. keratin from hair and skin), or from reagents (e.g. trypsin), that are required to prepare samples for analysis. We found that a significant amount of MS instrument time was spent sequencing peptides from abundant contaminant proteins. While completely eliminating non-specific protein contamination is not feasible, it is possible to reduce the sequencing of these contaminants. For example, exclusion lists can provide a list of masses that can be used to instruct the mass spectrometer to ‘ignore’ the undesired contaminant peptides in the list. We empirically generated be-spoke exclusion lists for several model organisms (Homo sapiens, Caenorhabditis elegans, Saccharomyces cerevisiae and Xenopus laevis), utilising information from over 500 mass spectrometry runs and cumulative analysis of these data. Here we show that by employing these empirically generated lists, it was possible to reduce the time spent analysing contaminating peptides in a given sample thereby facilitating more efficient data acquisition and analysis.

Biological significance

Given the current efficacy of the Mass Spectrometry instrumentation, the utilisation of data from ~500 mass spec runs to generate be-spoke exclusion lists and optimise data acquisition is the significance of this manuscript.

This article is part of a Special Issue entitled: New Horizons and Applications for Proteomics [EuPA 2012].

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We looked at the contribution of ‘contaminating’ peptides to MS acquisition time.

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We found that 30–50% of time was wasted on contaminant peptide sequencing.

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We tested whether the application of an exclusion list would solve this problem.

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Exclusion lists generated for specific species from > 500 mass spectrometry runs.

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Exclusion lists enabled more efficient analysis with coverage and isoform data.

A proteomics and transcriptomics approach to identify leukemic stem cell (LSC) markers

Interactions between hematopoietic stem cells and their niche are mediated by proteins within the plasma membrane (PM) and changes in these interactions might alter hematopoietic stem cell fate and ultimately result in acute myeloid leukemia (AML). Here, using nano-LC/MS/MS, we set out to analyze the PM profile of two leukemia patient samples. We identified 867 and 610 unique CD34(+) PM (-associated) proteins in these AML samples respectively, including previously described proteins such as CD47, CD44, CD135, CD96, and ITGA5, but also novel ones like CD82, CD97, CD99, PTH2R, ESAM, MET, and ITGA6. Further validation by flow cytometry and functional studies indicated that long-term self-renewing leukemic stem cells reside within the CD34(+)/ITGA6(+) fraction, at least in a subset of AML cases. Furthermore, we combined proteomics with transcriptomics approaches using a large panel of AML CD34(+) (n = 60) and normal bone marrow CD34(+) (n = 40) samples. Thus, we identified eight subgroups of AML patients based on their specific PM expression profile. GSEA analysis revealed that these eight subgroups are enriched for specific cellular processes.